Posts tagged ‘variable selection’

[ArXiv] classifying spectra

Variable Selection and Updating In Model-Based Discriminant Analysis for High Dimensional Data with Food Authenticity Applications
by Murphy, Dean, and Raftery

Classifying or clustering (or semi supervised learning) spectra is a very challenging problem from collecting statistical-analysis-ready data to reducing the dimensionality without sacrificing complex information in each spectrum. Not only how to estimate spiky (not differentiable) curves via statistically well defined procedures of estimating equations but also how to transform data that match the regularity conditions in statistics is challenging.
Continue reading ‘[ArXiv] classifying spectra’ »


Approximately for a decade, there have been journals dedicated to bioinformatics. On the other hand, there is none in astronomy although astronomers have a long history of comprising a huge volume of catalogs and data archives. Prof. Bickel’s comment during his plenary lecture at the IMS-APRM particularly on sparse matrix and philosophical issues on choosing principal components led me to wonder why astronomers do not discuss astroinformatics. Continue reading ‘Astroinformatics’ »